The present embodiments relate to magnetic resonance imaging data collection and processing, and more specifically, to methods for accelerating magnetic resonance data collection and synthesizing motion-corrected images from the collected data.
In general, magnetic resonance imaging (MRI) examinations are based on the interactions among a primary magnetic field, a radiofrequency (RF) magnetic field and time varying magnetic gradient fields with gyromagnetic material having nuclear spins within a subject of interest, such as a patient. Certain gyromagnetic materials, such as hydrogen nuclei in water molecules, have characteristic behaviors in response to external magnetic fields. The precession of spins of these nuclei can be influenced by manipulation of the fields to produce RF signals that can be detected, processed, and used to reconstruct a useful image.
The magnetic fields used to generate images in MRI systems include a highly uniform, static magnetic field that is produced by a primary magnet. A series of gradient fields are produced by a set of gradient coils located around the subject. The gradient fields encode positions of individual plane or volume elements (pixels or voxels) in two or three dimensions. An RF coil is employed to produce an RF magnetic field. This RF magnetic field perturbs the spins of some of the gyromagnetic nuclei from their equilibrium directions, causing the spins to precess around the axis of their equilibrium magnetization. During this precession, RF fields are emitted by the spinning, precessing nuclei and are detected by either the same transmitting RF coil, or by a separate coil. These signals are amplified, filtered, and digitized. The digitized signals are then processed using one or more algorithms to reconstruct a useful image.
Techniques have been developed to perform MRI imaging sequences quickly, so as to avoid long breath holds required of patients, to obtain images of rapidly changing anatomies (e.g., the beating heart), and/or to monitor the flow of one or more fluids (e.g., contrast agents) through various anatomies. Some such techniques acquire less than all of the information normally utilized for image reconstruction, requiring that the absent data be estimated in some way for proper, high quality image creation. However, current techniques for such estimation are often inadequate or subject to further improvement. For example, it can be difficult to obtain clinically useful images using accelerated imaging techniques in situations where the patient being imaged is moving. As an example, during the time in which magnetic resonance (MR) data is obtained, the patient may be moving, which can cause blurring and other artifacts in an image reproduced from the MR data. Indeed, even in situations in which acquisition is accelerated, patient motion may be problematic for image reconstruction. Accordingly, it is now recognized that a need exists for improved methods for data acquisition, estimation, and reconstruction in magnetic resonance imaging techniques that are sensitive to patient motion.